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e2tree: Explainable Ensemble Trees
The Explainable Ensemble Trees 'e2tree' approach has been proposed by Aria et al. (2024) <doi:10.1007/s00180-022-01312-6>. It aims to explain and interpret decision tree ensemble models using a single tree-like structure. 'e2tree' is a new way of explaining an ensemble tree trained through 'randomForest' or 'xgboost' packages.
Getting started
Browse package contents
Package details |
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| Author | Massimo Aria [aut, cre, cph] (<https://orcid.org/0000-0002-8517-9411>), Agostino Gnasso [aut] (<https://orcid.org/0000-0002-8046-3923>) |
| Maintainer | Massimo Aria <aria@unina.it> |
| License | MIT + file LICENSE |
| Version | 0.1.2 |
| URL | https://github.com/massimoaria/e2tree |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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